Patrick MacInnes
Most of the things I care about start with the same question: how does this work, and how do I know whether it works well?
I am a student in Grand Junction, Colorado, completing a double major in Computer Information Systems and Finance at Colorado Mesa University, with graduation expected in May 2027. That question shows up in school, in internship work at Tresic and Reiter USA, and in the projects I build on my own. The part of AI work I care about most is evaluation: defining what good means, measuring behavior, and knowing when the evidence is strong enough to trust.
My LLM Judge Eval Harness is the clearest public example. It calibrates a quality threshold, measures held-out precision, estimates uncertainty, and intentionally fails when a promising score is not supported by enough evidence. Other projects, from Nihongo Sensei to Webhook Lab, let me explore different kinds of systems end to end. Browse all of them on projects.
Outside school and work, I follow curiosity into subjects that do not obviously connect, including markets. I make Frenchcore remixes, return to anime, manga, and related stories, and have been a swimmer for most of my life. I want room for more than one thing without turning every interest into career optimization.
After graduation, I want to work on software and AI systems where evaluation matters: defining what good looks like, measuring behavior, and turning results into systems people can trust. I am open to full-time software engineering and AI/ML roles, especially in the Denver metro area or with relocation support.